Overview

Dataset statistics

Number of variables8
Number of observations35701
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 MiB
Average record size in memory72.0 B

Variable types

TimeSeries8

Timeseries statistics

Number of series8
Time series length35701
Starting point2011-08-25 15:00:00
Ending point2016-06-30 00:00:00
Period1 hour, 11 minutes and 25.21 seconds
2023-10-11T22:02:58.050655image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:59.237778image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Alerts

b is highly overall correlated with b_modelHigh correlation
br_model is highly overall correlated with bt_modelHigh correlation
bt_model is highly overall correlated with br_modelHigh correlation
b_model is highly overall correlated with bHigh correlation
br is non stationaryNon stationary
bt is non stationaryNon stationary
bn is non stationaryNon stationary
b is non stationaryNon stationary
br_model is non stationaryNon stationary
bt_model is non stationaryNon stationary
b_model is non stationaryNon stationary
br is seasonalSeasonal
bt is seasonalSeasonal
bn is seasonalSeasonal
b is seasonalSeasonal
br_model is seasonalSeasonal
bt_model is seasonalSeasonal
b_model is seasonalSeasonal

Reproduction

Analysis started2023-10-12 05:01:43.558801
Analysis finished2023-10-12 05:02:57.816516
Duration1 minute and 14.26 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

br
Numeric time series

NON STATIONARY  SEASONAL 

Distinct35586
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.057298055
Minimum-10.2545
Maximum7.1895
Zeros0
Zeros (%)0.0%
Memory size557.8 KiB
2023-10-11T22:02:59.444858image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum-10.2545
5-th percentile-1.6481667
Q1-0.40866667
median-0.019833333
Q30.31416667
95-th percentile1.3676667
Maximum7.1895
Range17.444
Interquartile range (IQR)0.72283333

Descriptive statistics

Standard deviation1.0220834
Coefficient of variation (CV)-17.838012
Kurtosis7.8965907
Mean-0.057298055
Median Absolute Deviation (MAD)0.36066667
Skewness-0.11993516
Sum-2045.5979
Variance1.0446544
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value2.679353725 × 10-30
2023-10-11T22:02:59.565878image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2023-10-11T22:02:59.915395image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Gap statistics

number of gaps50
min3 hours
max13 weeks, 4 days and 12 hours
mean5 days, 16 hours and 38 minutes
std2 weeks, 19 hours and 57 minutes
2023-10-11T22:03:00.039017image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ValueCountFrequency (%)
0.14 6
 
< 0.1%
0.04 6
 
< 0.1%
0.22 5
 
< 0.1%
0.2 5
 
< 0.1%
-0.24 4
 
< 0.1%
-0.58 4
 
< 0.1%
-0.33 4
 
< 0.1%
0.42 3
 
< 0.1%
0.35 3
 
< 0.1%
1.39 2
 
< 0.1%
Other values (35576) 35659
99.9%
ValueCountFrequency (%)
-10.2545 1
< 0.1%
-9.950666667 1
< 0.1%
-9.524 1
< 0.1%
-9.057226891 1
< 0.1%
-8.20725 1
< 0.1%
-7.749083333 1
< 0.1%
-7.671666667 1
< 0.1%
-7.091833333 1
< 0.1%
-6.867142857 1
< 0.1%
-6.75025 1
< 0.1%
ValueCountFrequency (%)
7.1895 1
< 0.1%
6.823583333 1
< 0.1%
6.785333333 1
< 0.1%
6.716666667 1
< 0.1%
6.6835 1
< 0.1%
6.658916667 1
< 0.1%
6.656333333 1
< 0.1%
6.601833333 1
< 0.1%
6.592666667 1
< 0.1%
6.559083333 1
< 0.1%
2023-10-11T22:02:59.736821image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ACF and PACF

bt
Numeric time series

NON STATIONARY  SEASONAL 

Distinct35612
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.023384865
Minimum-20.29975
Maximum15.309333
Zeros0
Zeros (%)0.0%
Memory size557.8 KiB
2023-10-11T22:03:00.211385image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum-20.29975
5-th percentile-2.3305833
Q1-0.70908333
median-0.0095833333
Q30.76775
95-th percentile2.4646667
Maximum15.309333
Range35.609083
Interquartile range (IQR)1.4768333

Descriptive statistics

Standard deviation1.5743696
Coefficient of variation (CV)67.324297
Kurtosis10.437013
Mean0.023384865
Median Absolute Deviation (MAD)0.73758333
Skewness-0.53699688
Sum834.86308
Variance2.4786397
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0
2023-10-11T22:03:00.317978image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2023-10-11T22:03:00.651377image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Gap statistics

number of gaps50
min3 hours
max13 weeks, 4 days and 12 hours
mean5 days, 16 hours and 38 minutes
std2 weeks, 19 hours and 57 minutes
2023-10-11T22:03:00.765222image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ValueCountFrequency (%)
2.06 3
 
< 0.1%
-0.82 3
 
< 0.1%
2.12 3
 
< 0.1%
-0.5288333333 2
 
< 0.1%
-1.21 2
 
< 0.1%
-1.02 2
 
< 0.1%
0.16175 2
 
< 0.1%
1.048333333 2
 
< 0.1%
-0.21 2
 
< 0.1%
-0.14 2
 
< 0.1%
Other values (35602) 35678
99.9%
ValueCountFrequency (%)
-20.29975 1
< 0.1%
-20.19741667 1
< 0.1%
-19.65391667 1
< 0.1%
-19.21816667 1
< 0.1%
-19.1225 1
< 0.1%
-17.52941667 1
< 0.1%
-17.13691667 1
< 0.1%
-16.70491667 1
< 0.1%
-15.49633333 1
< 0.1%
-14.64941667 1
< 0.1%
ValueCountFrequency (%)
15.30933333 1
< 0.1%
13.64941667 1
< 0.1%
11.82125 1
< 0.1%
10.87366667 1
< 0.1%
10.17233333 1
< 0.1%
10.03741667 1
< 0.1%
9.985166667 1
< 0.1%
9.7 1
< 0.1%
9.25302521 1
< 0.1%
9.199333333 1
< 0.1%
2023-10-11T22:03:00.474545image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ACF and PACF

bn
Numeric time series

NON STATIONARY  SEASONAL 

Distinct35617
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.024109498
Minimum-13.577333
Maximum14.446917
Zeros0
Zeros (%)0.0%
Memory size557.8 KiB
2023-10-11T22:03:00.938209image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum-13.577333
5-th percentile-1.5559375
Q1-0.33125
median0.0044166667
Q30.36108333
95-th percentile1.6790833
Maximum14.446917
Range28.02425
Interquartile range (IQR)0.69233333

Descriptive statistics

Standard deviation1.1260729
Coefficient of variation (CV)46.70661
Kurtosis14.500441
Mean0.024109498
Median Absolute Deviation (MAD)0.34641667
Skewness0.11710488
Sum860.7332
Variance1.2680402
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0
2023-10-11T22:03:01.059573image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2023-10-11T22:03:01.427341image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Gap statistics

number of gaps50
min3 hours
max13 weeks, 4 days and 12 hours
mean5 days, 16 hours and 38 minutes
std2 weeks, 19 hours and 57 minutes
2023-10-11T22:03:01.544627image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ValueCountFrequency (%)
-0.17 5
 
< 0.1%
-0.01 4
 
< 0.1%
-0.41 4
 
< 0.1%
-0.42 4
 
< 0.1%
0.4686666667 2
 
< 0.1%
-0.8040833333 2
 
< 0.1%
-0.31 2
 
< 0.1%
-0.45 2
 
< 0.1%
-2.15 2
 
< 0.1%
-2.22 2
 
< 0.1%
Other values (35607) 35672
99.9%
ValueCountFrequency (%)
-13.57733333 1
< 0.1%
-13.09333333 1
< 0.1%
-12.66691667 1
< 0.1%
-11.93616667 1
< 0.1%
-11.88991597 1
< 0.1%
-10.86588235 1
< 0.1%
-9.652083333 1
< 0.1%
-9.6155 1
< 0.1%
-9.590583333 1
< 0.1%
-9.205583333 1
< 0.1%
ValueCountFrequency (%)
14.44691667 1
< 0.1%
12.0765 1
< 0.1%
12.03241667 1
< 0.1%
10.9310084 1
< 0.1%
10.69125 1
< 0.1%
10.09033333 1
< 0.1%
9.8385 1
< 0.1%
9.744833333 1
< 0.1%
9.476333333 1
< 0.1%
9.4435 1
< 0.1%
2023-10-11T22:03:01.240427image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ACF and PACF

b
Numeric time series

HIGH CORRELATION  NON STATIONARY  SEASONAL 

Distinct35661
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6078705
Minimum0.019858702
Maximum20.707437
Zeros0
Zeros (%)0.0%
Memory size557.8 KiB
2023-10-11T22:03:01.705661image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum0.019858702
5-th percentile0.29221759
Q10.65496303
median1.1532781
Q32.0400392
95-th percentile4.4996181
Maximum20.707437
Range20.687579
Interquartile range (IQR)1.3850762

Descriptive statistics

Standard deviation1.4867501
Coefficient of variation (CV)0.92467031
Kurtosis15.492809
Mean1.6078705
Median Absolute Deviation (MAD)0.60399311
Skewness2.8630705
Sum57402.584
Variance2.2104258
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value2.579342017 × 10-29
2023-10-11T22:03:01.806341image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2023-10-11T22:03:02.140906image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Gap statistics

number of gaps50
min3 hours
max13 weeks, 4 days and 12 hours
mean5 days, 16 hours and 38 minutes
std2 weeks, 19 hours and 57 minutes
2023-10-11T22:03:02.256040image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ValueCountFrequency (%)
0.7485318964 2
 
< 0.1%
1.491643389 2
 
< 0.1%
1.548805992 2
 
< 0.1%
2.837005464 2
 
< 0.1%
3.199328054 2
 
< 0.1%
2.173131381 2
 
< 0.1%
1.583066644 2
 
< 0.1%
1.547707983 2
 
< 0.1%
0.5941380311 2
 
< 0.1%
1.15277925 2
 
< 0.1%
Other values (35651) 35681
99.9%
ValueCountFrequency (%)
0.01985870226 1
< 0.1%
0.02770454235 1
< 0.1%
0.03181947779 1
< 0.1%
0.05039193608 1
< 0.1%
0.05115954076 1
< 0.1%
0.05159188136 1
< 0.1%
0.0521709929 1
< 0.1%
0.05448024617 1
< 0.1%
0.05540162703 1
< 0.1%
0.05998900362 1
< 0.1%
ValueCountFrequency (%)
20.70743734 1
< 0.1%
20.6239479 1
< 0.1%
20.4531967 1
< 0.1%
20.12335926 1
< 0.1%
19.85538745 1
< 0.1%
19.49488985 1
< 0.1%
19.31214163 1
< 0.1%
19.29872414 1
< 0.1%
19.19273908 1
< 0.1%
18.56803008 1
< 0.1%
2023-10-11T22:03:01.978032image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ACF and PACF

br_model
Numeric time series

HIGH CORRELATION  NON STATIONARY  SEASONAL 

Distinct35556
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.002735914
Minimum-4.1819448
Maximum7.2738395
Zeros0
Zeros (%)0.0%
Memory size557.8 KiB
2023-10-11T22:03:02.414312image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum-4.1819448
5-th percentile-0.86633761
Q1-0.18128725
median0.0051343633
Q30.16589179
95-th percentile0.89818316
Maximum7.2738395
Range11.455784
Interquartile range (IQR)0.34717904

Descriptive statistics

Standard deviation0.61010885
Coefficient of variation (CV)223.00001
Kurtosis10.258184
Mean0.002735914
Median Absolute Deviation (MAD)0.17034455
Skewness0.628109
Sum97.674866
Variance0.37223281
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value6.061431392 × 10-30
2023-10-11T22:03:02.508735image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2023-10-11T22:03:02.847860image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Gap statistics

number of gaps50
min3 hours
max13 weeks, 4 days and 12 hours
mean5 days, 16 hours and 38 minutes
std2 weeks, 19 hours and 57 minutes
2023-10-11T22:03:02.954989image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ValueCountFrequency (%)
0.149824102 5
 
< 0.1%
-0.1292337186 4
 
< 0.1%
0.1108384048 3
 
< 0.1%
0.08327461234 3
 
< 0.1%
0.2916140036 3
 
< 0.1%
0.2976745089 3
 
< 0.1%
-0.1465154648 3
 
< 0.1%
-0.05918415445 3
 
< 0.1%
-0.1283720132 3
 
< 0.1%
-0.007702284456 3
 
< 0.1%
Other values (35546) 35668
99.9%
ValueCountFrequency (%)
-4.181944777 1
< 0.1%
-4.171477983 1
< 0.1%
-4.166662099 1
< 0.1%
-4.161274586 1
< 0.1%
-4.157076414 1
< 0.1%
-4.152095694 1
< 0.1%
-4.128219921 1
< 0.1%
-4.065932526 1
< 0.1%
-3.991795764 1
< 0.1%
-3.876041013 1
< 0.1%
ValueCountFrequency (%)
7.273839535 1
< 0.1%
7.107620184 1
< 0.1%
5.55358406 1
< 0.1%
4.586980036 1
< 0.1%
4.406029355 1
< 0.1%
4.226410125 1
< 0.1%
4.225827226 1
< 0.1%
4.224360322 1
< 0.1%
4.201212647 1
< 0.1%
4.184303146 1
< 0.1%
2023-10-11T22:03:02.678221image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ACF and PACF

bt_model
Numeric time series

HIGH CORRELATION  NON STATIONARY  SEASONAL 

Distinct35556
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.038432322
Minimum-12.065577
Maximum7.2587683
Zeros0
Zeros (%)0.0%
Memory size557.8 KiB
2023-10-11T22:03:03.107600image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum-12.065577
5-th percentile-1.7197686
Q1-0.58713977
median-0.062868907
Q30.52681712
95-th percentile1.6034869
Maximum7.2587683
Range19.324346
Interquartile range (IQR)1.1139569

Descriptive statistics

Standard deviation1.1145604
Coefficient of variation (CV)-29.000599
Kurtosis5.8533794
Mean-0.038432322
Median Absolute Deviation (MAD)0.55554336
Skewness-0.27425974
Sum-1372.0723
Variance1.2422448
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value5.507553617 × 10-30
2023-10-11T22:03:03.208812image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2023-10-11T22:03:03.536856image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Gap statistics

number of gaps50
min3 hours
max13 weeks, 4 days and 12 hours
mean5 days, 16 hours and 38 minutes
std2 weeks, 19 hours and 57 minutes
2023-10-11T22:03:03.649725image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ValueCountFrequency (%)
-1.324604748 5
 
< 0.1%
1.039741625 4
 
< 0.1%
-0.7814594347 3
 
< 0.1%
-0.7740874233 3
 
< 0.1%
-1.171388182 3
 
< 0.1%
-1.558553781 3
 
< 0.1%
0.03177701314 3
 
< 0.1%
0.3971375528 3
 
< 0.1%
0.4958332645 3
 
< 0.1%
0.1684973733 3
 
< 0.1%
Other values (35546) 35668
99.9%
ValueCountFrequency (%)
-12.06557742 1
< 0.1%
-9.138278575 1
< 0.1%
-8.415557449 1
< 0.1%
-8.368168759 1
< 0.1%
-8.358258446 1
< 0.1%
-8.265330983 1
< 0.1%
-8.1849667 1
< 0.1%
-8.14900019 1
< 0.1%
-8.06647433 1
< 0.1%
-8.048770709 1
< 0.1%
ValueCountFrequency (%)
7.258768319 1
< 0.1%
7.189141988 1
< 0.1%
7.06832682 1
< 0.1%
6.863515915 1
< 0.1%
6.66180698 1
< 0.1%
6.660993079 1
< 0.1%
6.355432577 1
< 0.1%
6.352601246 1
< 0.1%
6.265343196 1
< 0.1%
6.179410565 1
< 0.1%
2023-10-11T22:03:03.365276image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ACF and PACF

bn_model
Numeric time series

Distinct5322
Distinct (%)14.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0070832908
Minimum-6.56
Maximum5.2
Zeros0
Zeros (%)0.0%
Memory size557.8 KiB
2023-10-11T22:03:04.275721image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum-6.56
5-th percentile-0.766
Q1-0.146
median0.00304
Q30.14
95-th percentile0.781
Maximum5.2
Range11.76
Interquartile range (IQR)0.286

Descriptive statistics

Standard deviation0.54750799
Coefficient of variation (CV)77.29571
Kurtosis13.807305
Mean0.0070832908
Median Absolute Deviation (MAD)0.14204
Skewness0.59946168
Sum252.88056
Variance0.299765
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0
2023-10-11T22:03:04.369824image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2023-10-11T22:03:04.680100image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Gap statistics

number of gaps50
min3 hours
max13 weeks, 4 days and 12 hours
mean5 days, 16 hours and 38 minutes
std2 weeks, 19 hours and 57 minutes
2023-10-11T22:03:04.783564image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ValueCountFrequency (%)
0.108 67
 
0.2%
0.103 61
 
0.2%
-0.102 59
 
0.2%
0.107 57
 
0.2%
0.124 56
 
0.2%
0.115 56
 
0.2%
-0.101 55
 
0.2%
0.104 55
 
0.2%
0.11 54
 
0.2%
0.105 53
 
0.1%
Other values (5312) 35128
98.4%
ValueCountFrequency (%)
-6.56 2
< 0.1%
-6.09 1
< 0.1%
-6.05 1
< 0.1%
-5.39 1
< 0.1%
-4.89 1
< 0.1%
-4.42 1
< 0.1%
-4.41 1
< 0.1%
-4.39 1
< 0.1%
-4.38 1
< 0.1%
-4.37 1
< 0.1%
ValueCountFrequency (%)
5.2 1
< 0.1%
5.16 1
< 0.1%
5.14 1
< 0.1%
5.02 1
< 0.1%
4.95 1
< 0.1%
4.94 1
< 0.1%
4.9 1
< 0.1%
4.8 1
< 0.1%
4.54 1
< 0.1%
4.48 1
< 0.1%
2023-10-11T22:03:04.522540image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ACF and PACF

b_model
Numeric time series

HIGH CORRELATION  NON STATIONARY  SEASONAL 

Distinct35661
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0066801
Minimum0.019014721
Maximum14.129873
Zeros0
Zeros (%)0.0%
Memory size557.8 KiB
2023-10-11T22:03:04.932711image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum0.019014721
5-th percentile0.13364733
Q10.3895344
median0.75085857
Q31.2661967
95-th percentile2.8377639
Maximum14.129873
Range14.110858
Interquartile range (IQR)0.87666229

Descriptive statistics

Standard deviation0.94991792
Coefficient of variation (CV)0.94361445
Kurtosis10.87225
Mean1.0066801
Median Absolute Deviation (MAD)0.41245934
Skewness2.5898503
Sum35939.488
Variance0.90234406
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value3.354611585 × 10-24
2023-10-11T22:03:05.029993image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2023-10-11T22:03:05.354103image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Gap statistics

number of gaps50
min3 hours
max13 weeks, 4 days and 12 hours
mean5 days, 16 hours and 38 minutes
std2 weeks, 19 hours and 57 minutes
2023-10-11T22:03:05.467099image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ValueCountFrequency (%)
0.6489761167 2
 
< 0.1%
0.719826368 2
 
< 0.1%
2.6375936 2
 
< 0.1%
0.2551436654 2
 
< 0.1%
1.343735465 2
 
< 0.1%
2.182521478 2
 
< 0.1%
0.6932488731 2
 
< 0.1%
1.204355429 2
 
< 0.1%
0.6853794569 2
 
< 0.1%
0.7730530383 2
 
< 0.1%
Other values (35651) 35681
99.9%
ValueCountFrequency (%)
0.01901472061 1
< 0.1%
0.01931946428 1
< 0.1%
0.01936951471 1
< 0.1%
0.0194235038 1
< 0.1%
0.01960734811 1
< 0.1%
0.01965583435 1
< 0.1%
0.02001605356 1
< 0.1%
0.02018417449 1
< 0.1%
0.02059897085 1
< 0.1%
0.02104917101 1
< 0.1%
ValueCountFrequency (%)
14.12987261 1
< 0.1%
11.58036269 1
< 0.1%
9.940372226 1
< 0.1%
9.576826197 1
< 0.1%
9.548701482 1
< 0.1%
9.478865966 1
< 0.1%
9.396728154 1
< 0.1%
9.325009383 1
< 0.1%
9.21027144 1
< 0.1%
9.190794307 1
< 0.1%
2023-10-11T22:03:05.183832image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ACF and PACF

Interactions

2023-10-11T22:02:57.255068image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:54.150458image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:54.600285image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:55.039051image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:55.527218image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:55.936079image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:56.358491image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:56.835487image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:57.309003image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:54.212056image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:54.657281image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:55.091813image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:55.581043image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:55.990561image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:56.416424image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:56.892099image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:57.364693image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:54.269431image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:54.714869image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:55.209565image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:55.633913image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:56.043525image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:56.476208image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:56.946514image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:57.416047image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:54.322555image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:54.767783image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:55.263117image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:55.682579image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:56.093933image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:56.530672image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:56.999436image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:57.463816image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:54.375358image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:54.818241image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:55.313175image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:55.728598image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:56.143792image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:56.582901image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:57.046439image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:57.516515image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:54.429627image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:54.871819image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:55.362625image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:55.779285image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:56.195337image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:56.643584image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:57.094350image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:57.572744image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:54.487593image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:54.930942image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:55.419511image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:55.835073image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:56.251841image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:56.718164image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:57.153263image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:57.623798image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:54.543866image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:54.983978image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:55.472000image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:55.885069image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:56.303526image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:56.773834image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-11T22:02:57.201283image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Correlations

2023-10-11T22:03:05.562682image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
brbtbnbbr_modelbt_modelbn_modelb_model
br1.000-0.359-0.050-0.0330.286-0.2690.004-0.034
bt-0.3591.000-0.0220.056-0.3600.4240.0060.044
bn-0.050-0.0221.0000.025-0.024-0.0100.0350.038
b-0.0330.0560.0251.000-0.0160.030-0.0390.537
br_model0.286-0.360-0.024-0.0161.000-0.6770.0070.013
bt_model-0.2690.424-0.0100.030-0.6771.0000.023-0.023
bn_model0.0040.0060.035-0.0390.0070.0231.000-0.021
b_model-0.0340.0440.0380.5370.013-0.023-0.0211.000

Missing values

2023-10-11T22:02:57.695610image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
A simple visualization of nullity by column.
2023-10-11T22:02:57.768680image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

brbtbnbbr_modelbt_modelbn_modelb_model
time
2011-08-25 15:00:00-1.8009761.8002440.5885372.613574-0.5340511.9043810.63202.076367
2011-08-25 16:00:00-1.8816832.2062381.1654463.125137-0.7251922.2858110.28102.414497
2011-08-25 17:00:00-1.6853042.1541742.0267833.404198-1.0377592.1467880.15702.389621
2011-08-25 18:00:00-2.0350001.3929821.7443863.020680-0.8455281.8575540.45802.091695
2011-08-25 19:00:00-2.8524370.8189921.0035293.132765-0.7337031.6853790.42001.885530
2011-08-25 20:00:00-2.1620831.8363330.9913333.004907-0.6897131.5819990.41201.774308
2011-08-25 21:00:00-1.6525002.7851671.1331673.431031-0.5060911.5951220.02431.673659
2011-08-25 22:00:00-2.3140002.4818330.5926673.444611-0.5334381.570054-0.22301.673127
2011-08-25 23:00:00-2.4735592.306017-0.2292373.389507-0.8136971.540221-0.13501.747172
2011-08-26 00:00:00-1.8126271.7216950.0241532.500087-0.9715511.421065-0.06741.722753
brbtbnbbr_modelbt_modelbn_modelb_model
time
2016-06-29 15:00:00-0.8019173.012083-0.5011673.1570370.008148-0.0859240.05880.104436
2016-06-29 16:00:00-0.6663333.076083-0.1175833.1496210.007953-0.0863950.05960.105259
2016-06-29 17:00:00-1.7599171.058917-0.4000002.0925130.007719-0.0870620.06030.106186
2016-06-29 18:00:00-0.776000-0.9259172.2629172.5652070.007387-0.0877100.06100.107092
2016-06-29 19:00:000.591250-0.7955004.4430004.5522130.007114-0.0885740.06160.108122
2016-06-29 20:00:001.711250-0.1335004.0133334.3649790.006723-0.0895160.06220.109211
2016-06-29 21:00:002.1151671.2990001.8905003.1201480.006411-0.0905750.06280.110403
2016-06-29 22:00:001.9417503.029000-0.8466673.6962250.006001-0.0916150.06340.111575
2016-06-29 23:00:001.9628704.493478-2.0917395.3310010.005552-0.0928520.06400.112908
2016-06-30 00:00:001.4132735.411455-3.3858186.5379620.005085-0.0940890.06450.114188